• The Korean Journal of Health Service Management
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• v.8 no.3
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• pp.207-218
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• 2014

This study was to compare the recognition of future career and nurse's characteristics according to nursing school system. This study was based on cross sectional descriptive method. The data were analyzed by $x^2$-test, t-test, and ANOVA using PASW WIN 18.0 program. The data represented that students who were doing associated degrees or bachelor degrees, showed the similar level recognition of future career and nurse's characteristics. However they showed differences in recognition of the career where they could create and new things(t=2.933, p=.004) and working part time(t=2.328, p=.021). In regards to recognition of nurse's characteristics bachelor degrees students had higher professional ethics($4.59{\pm}.44$). This study proposed that these research results could be used for improving methodology of nursing education.

• Journal of Digital Convergence
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• v.17 no.11
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• pp.557-567
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• 2019

This investigation was conducted to derive future recognition and future competency of career counselors using future workshops and to verify the effectiveness of improving future adaptability. For this purpose, the future workshop was conducted for 25 career counselors and the data written and the discussion contents of the future workshop were analyzed. For analysis, word frequency analysis and corresponding sample T-verification were conducted, and the main words were derived through consensus. The results, First, the keywords of future recognition showed high frequency of robot, artificial intelligence, leisure, education, convenience, and the disabled. Second, the future labor sites projected the most changes due to high technology. Third, at the career counseling site, professional career counselors and robot counselors related to the fourth industrial revolution are expected to appear. Fourth, future competencies of career counselors were derived from information processing ability, professional counseling ability, communication ability, and ethical consciousness. Finally, it was confirmed that the future adaptability of career counselors increases after participating in future workshops, and the future competencies derived from this study are expected to be used for job training of career counselors.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.46 no.1
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• pp.55-67
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• 2023

Lightweight face recognition models, as one of the most popular and long-standing topics in the field of computer vision, has achieved vigorous development and has been widely used in many real-world applications due to fewer number of parameters, lower floating-point operations, and smaller model size. However, few surveys reviewed lightweight models and reimplemented these lightweight models by using the same calculating resource and training dataset. In this survey article, we present a comprehensive review about the recent research advances on the end-to-end efficient lightweight face recognition models and reimplement several of the most popular models. To start with, we introduce the overview of face recognition with lightweight models. Then, based on the construction of models, we categorize the lightweight models into: (1) artificially designing lightweight FR models, (2) pruned models to face recognition, (3) efficient automatic neural network architecture design based on neural architecture searching, (4) Knowledge distillation and (5) low-rank decomposition. As an example, we also introduce the SqueezeFaceNet and EfficientFaceNet by pruning SqueezeNet and EfficientNet. Additionally, we reimplement and present a detailed performance comparison of different lightweight models on the nine different test benchmarks. At last, the challenges and future works are provided. There are three main contributions in our survey: firstly, the categorized lightweight models can be conveniently identified so that we can explore new lightweight models for face recognition; secondly, the comprehensive performance comparisons are carried out so that ones can choose models when a state-of-the-art end-to-end face recognition system is deployed on mobile devices; thirdly, the challenges and future trends are stated to inspire our future works.

• IEMEK Journal of Embedded Systems and Applications
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• v.6 no.4
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• pp.201-207
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• 2011

This paper introduces a novel concept of 'Emotional Communication' for future smart phone. While traditional information based communication technologies focus on how to precisely transmit the content of message, emotional communication is intended to support and augment social relationship among people and to comfort the user to be happy. In this paper, we propose future communication services and core technologies which can estimate emotional desire of users and respond to the desire to be happy with connectedness and consolation from peoples. Firstly, we introduce emotion recognition techniques to estimate emotional desire of users. At second, the emotional responding services are categorized to four parts and the details are shown. Lastly we propose the process to implement emotional communication system and the main techniques to fulfill the system requirements for future smart-phone services.

• Proceedings of the Korea Information Processing Society Conference
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• 2023.05a
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• pp.748-750
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• 2023

Facial expression recognition technology's rapid growth and development have garnered significant attention in recent years. This technology holds immense potential for various applications, making it crucial to stay up-to-date with the latest trends and advancements. Simultaneously, it is essential to identify and address the challenges that impede the technology's progress. Motivated by these factors, this study aims to understand the latest trends, future directions, and challenges in facial expression recognition technology by utilizing text mining to analyze papers published between 2020 and 2023. Our research focuses on discerning which aspects of these papers provide valuable insights into the field's recent developments and issues. By doing so, we aim to present the information in an accessible and engaging manner for readers, enabling them to understand the current state and future potential of facial expression recognition technology. Ultimately, our study seeks to contribute to the ongoing dialogue and facilitate further advancements in this rapidly evolving field.

• Journal of Information Processing Systems
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• v.17 no.6
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• pp.1138-1156
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• 2021

Emotional semantics are the highest level of semantics that can be extracted from an image. Constructing a system that can automatically recognize the emotional semantics from images will be significant for marketing, smart healthcare, and deep human-computer interaction. To understand the direction of image emotion recognition as well as the general research methods, we summarize the current development trends and shed light on potential future research. The primary contributions of this paper are as follows. We investigate the color, texture, shape and contour features used for emotional semantics extraction. We establish two models that map images into emotional space and introduce in detail the various processes in the image emotional semantic recognition framework. We also discuss important datasets and useful applications in the field such as garment image and image retrieval. We conclude with a brief discussion about future research trends.

• Journal of Korean Library and Information Science Society
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• v.25
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• pp.19-50
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• 1996

The purpose of this paper is to study on ownership and access in future library. For this purpose, this is criticized about recognition regarding future library of Library and Information Science researchers in Korea. And, this is reviewed the present stages of collection development and a role of future books, future libraries and future librarians in Korea. The result of this study is known unrealistic reality analysis and forecast surrounding future library discourse and at the same time that following Western model is not fit for future library in Korea. This study is proposed resolving of problems to access based on physical collection in future library.

• The Journal of the Korea Contents Association
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• v.20 no.7
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• pp.86-96
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• 2020

Based on the use cases of image recognition technology, this study looked at how artificial intelligence plays a role in image recognition technology. Through image recognition technology, satellite images can be analyzed with artificial intelligence to reveal the calculation of oil storage tanks in certain countries. And image recognition technology makes it possible for searching images or products similar to images taken or downloaded by users, as well as arranging fruit yields, or detecting plant diseases. Based on deep learning and neural network algorithms, we can recognize people's age, gender, and mood, confirming that image recognition technology is being applied in various industries. In this study, we can look at the use cases of domestic and overseas image recognition technology, as well as see which methods are being applied to the industry. In addition, through this study, the direction of future research was presented, focusing on various successful cases in which image recognition technology was implemented and applied in various industries. At the conclusion, it can be considered that the direction in which domestic image recognition technology should move forward in the future.

• Journal of Korean Library and Information Science Society
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• v.25
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• pp.1-18
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• 1996

The purpose of this paper is to study on ownership and access in future library. For this purpose, this is criticized about recognition regarding future library of Library and Information Science researchers in Korea. And this is reviewed the present stages of collection development and a role of future books, future libraries and future librarians in Korea. The result of this study is known unrealistic reality analysis and forecast surrounding future library discourse and at the same time that following Western model is not fit for future library in Korea. This study is proposed resolving of problems to access based on physical collection in future library.

• ETRI Journal
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• v.26 no.3
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• pp.273-276
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• 2004

We propose a novel feature processing technique which can provide a cepstral liftering effect in the log-spectral domain. Cepstral liftering aims at the equalization of variance of cepstral coefficients for the distance-based speech recognizer, and as a result, provides the robustness for additive noise and speaker variability. However, in the popular hidden Markov model based framework, cepstral liftering has no effect in recognition performance. We derive a filtering method in log-spectral domain corresponding to the cepstral liftering. The proposed method performs a high-pass filtering based on the decorrelation of filter-bank energies. We show that in noisy speech recognition, the proposed method reduces the error rate by 52.7% to conventional feature.